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发布者哺:文明办作者稳爽鸡:发布时间鼎汤:2019-06-27浏览次数感杜汹:1100


主讲人继免汇:魏颖颖 香港中文大学助理教授


时间吕淖膊:2019年6月29日13冉:00


地点拭苫:三号楼332会议厅


举办单位钡:数理学院


主讲人介绍泊:魏颖颖于2009年毕业于清华大学数学系暇,2014年在约翰霍普金斯大学获得计算机科学硕士学位及生物统计博士学位缉澜蔑,同年起在香港中文大学统计系任助理教授其。


内容介绍慰冠:In epigenome-wide association studies, the measured signals for each sample are  a mixture of methylation profiles from different cell types. The current  approaches to the association detection only claim whether a  cytosine-phosphate-guanine (CpG) site is associated with the phenotype or not,  but they cannot determine the cell type in which the risk-CpG site is affected  by the phenotype. Here, we propose a solid statistical method, HIgh REsolution  (HIRE), which not only substantially improves the power of association detection  at the aggregated level as compared to the existing methods but also enables the  detection of risk-CpG sites for individual cell types. We prove that the  proposed model is identifiable under conditions easily met in real data.

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